Collision detection and avoidance has expanded robot autonomy by allowing robots to move in three dimensional space. Robots can detect and avoid obstacles in their path while also finding and interacting with items of interest. The expanded autonomy has increased the functionality and roles of robots. One such example is the use of robots to navigate within a warehouse in order to retrieve items distributed throughout the warehouse.
Collision detection and avoidance is a form of local navigation. Robots independently identify obstacles and independently perform actions to avoid the obstacles. Such local navigational techniques are sufficient for robots navigating in a space with stationary obstacles. Inefficiencies and even deadlocks can arise however when local navigational techniques fully control robot movements in a space with transitory obstacles. In particular, inefficiencies and deadlocks can be seen when the local navigational techniques fully control movements of several robots operating in the same space. The inefficiencies and deadlocks stem from the lack of coordinated movement between the robots and the inability of the robots to communicate in order to establish movement precedence. For example, a first robot locally navigating away from a collision can create a ripple effect whereby the first robot moves into the path of a second robot, creating one or more new collisions that both the first and second robots attempt to avoid, which in turn cascades the effect and creates additional obstacles with other robots.
Generally, the same issues arise whenever two or more robots require the same resource and the robots operate independently and autonomously. The sought after resource can include anything including tangible and intangible resources. Tangible assets include physical items, locations (e.g., space, charging stations, etc.), and components. Intangible assets can include shared computing resources, shared communication channels, and time as some examples.
There is therefore a need to optimize access to limited resources for robots operating in the same space. The optimized access will allow the robots to move more efficiently within a common space as well as perform designated tasks more efficiently. In particular, the optimized access prioritizes the resource allocation to minimize aggregate time robots wait in order to obtain the resources needed to move or perform a task. To this end, there is a need to coordinate the resource allocation and reservation amongst robots. There is a further need to have the robots coordinate the resource allocation and reservation autonomously without human intervention so that the resources can be efficiently allocated in real-time. Accordingly, there is a need to supplement local navigational techniques with global navigational techniques and independent and autonomous robot operation through coordinated resource allocation.